The influence of epiphylls on remote sensing of humid forests

Epiphylls - lichens, fungi, liverworts, etc. infesting leaf surfaces - are found throughout humid forests of the world. It is well understood that epiphylls inhibit light interception by host plants, but their effect on remote sensing of colonized forests has not been examined. Incorporating leaf-level spectra from Terra Firme (primary forest) and Amazonian Caatinga (woodlands/forest growing on nutrient-deficient sandy soils), we used the GeoSAIL model to propagate leaf-level measurements to the canopy level and determine their effect on commonly used vegetation indices. In Caatinga, moderate infestations (50% leaf area epiphyll cover), lowered simulated Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) values by 6.1% and 20.4%, respectively, largely due to near infrared dampening. Heavy infestation (100% cover) simulations exhibited decreases 1.5-2 times greater than those of moderate infestations. For Terra Firme, which are generally less affected by epiphylls, moderate (20% leaf area) and heavy infestations (40%) lowered EVI by 4.4% (S.D. 0.8%) and 8.1% (S.D. 1.5%), respectively. Near infrared and green reflectance were most affected at the canopy level, showing mean decreases of 10.6% (S.D. 2.25%) and 9.5% (S.D. 3.49%), respectively, in heavy Terra Firme infestations. Time series of Moderate Resolution Imaging Spectrometer (MODIS) data corroborated the modeling results, suggesting a degree of coupling between epiphyll cover and the EVI and NDVI. These results suggest that, without explicit consideration of the presence of epiphylls, remote sensing-based methodologies may underestimate leaf area index, biomass and productivity in humid forests.     

Fracture resistance via topology optimization

The fracture resistance of structures is optimized using the level-set method. Fracture resistance is assumed to be related to the elastic energy released by a crack propagating in a normal direction from parts of the boundary that are in tension, and is calculated using the virtual crack extension technique. The shape derivative of the fracture-resistance objective function is derived. Two illustrative two-dimensional case studies are presented: a hole in a plate subjected to biaxial strain; and a bridge fixed at both ends subjected to a single load in which the compliance and fracture resistance are jointly optimized. The structures obtained have rounded corners and more material at places where they are in tension. Based on the results, we propose that fracture resistance may be modeled more easily but less directly by including a term proportional to surface area in the objective function, in conjunction with nonlinear elasticity where the Young’s modulus in tension is lower than in compression.     

Dynamic models for nonstationary signal segmentation.

This paper investigates Hidden Markov Models (HMMs) in which the observations are generated from an autoregressive (AR) model. The overall model performs nonstationary spectral analysis and automatically segments a time series into discrete dynamic regimes. Because learning in HMMs is sensitive to initial conditions, we initialize the HMM model with parameters derived from a cluster analysis of Kalman filter coefficients. An important aspect of the Kalman filter implementation is that the state noise is estimated on-line. This allows for an initial estimation of AR parameters for each of the different dynamic regimes. These estimates are then fine-tuned with the HMM model. The method is demonstrated on a number of synthetic problems and on electroencephalogram data.     

TRICLOPS: A tool for studying active vision

The design, performance, and application of The Real-time, Intelligently ControLled, Optical Positioning System (TRICLOPS) are described in this article. TRICLOPS is a multiresolution trinocular camera-pointing system which provides a center wide-angle view camera and two higher-resolution vergence cameras. It is a direct-drive system that exhibits dynamic performance comparable to the human visual system. The mechanical design and performance of various active vision systems are discussed and compared to those of TRICLOPS. The multiprocessor control system for TRICLOPS is described. The kinematics of the device are also discussed and calibration methods are given. Finally, as an example of real-time visual control, a problem in visual tracking with TRICLOPS is examined. In this example, TRICLOPS is shown to be capable of tracking a ball moving at 3 m/s, which results in rotational velocities of the vergence cameras in excess of 6 rad/s (344 deg/s).     

Integrating high resolution remote sensing,GIS and fuzzy set theory for identifying susceptibility areas of forest insect infestations

The use of fuzzy set theory has become common in remote sensing and geographical information system (GIS) applications to deal with issues surrounding the uncertainty of geospatial datasets. The objective of this study is to develop a model that integrates the concept of fuzzy set theory with remote sensing and GIS in order to produce susceptibility maps of insect infestations in forest landscapes. Fuzzy set theory was applied to information extracted from multiple‐year high resolution remote sensing data and integrated in a raster‐based GIS to create a map indicating the spatial variation of insect susceptibility in a landscape. Variable‐specific fuzzy membership functions were developed based on expert knowledge and existing data, and integrated through a semantic import model. The results from a case study on mountain pine beetle (Dendroctonus ponderosae Hopkins) illustrate that the model provides a method to successfully estimate areas of varying susceptibility to insect infestation from high resolution remote sensing images. It was concluded that fuzzy sets are an adequate method for dealing with uncertainty in defining susceptibility variables. The susceptibility maps can be utilized for guiding management decisions based on the spatial aspects of insect–host relationships.     

Jitter in ATM networks and its impact on peak rate enforcement

Cells arriving to an ATM network experience random delays due to queueing in upstream multiplexing stages, notably in customer premises. This is the phenomenon of jitter and the aim of the present paper is to study its influence on peak rate enforcement. We first introduce some general characterizations of jitter and then, describe two models of jittered flows based on simple queueing systems. We discuss the objectives of peak rate enforcement and study the impact of jitter on the dimensioning of jumping window and leaky bucket mechanisms. A useful synthetic characterization of jitter appears to be a remote quantile of the cell delay distribution expressed in units of the initial inter-cell interval.     

Identification of central Kenyan Rift Valley Fever virus vector habitats with landsat TM and evaluation of their flooding status with airborne imaging radar

Rift Valley Fever (RVF) is a mosquito-borne virus that affects livestock and humans in Africa. Landsat Thematic Mapper (TM) data are shown to be effective in identifying dambos, intermittently flooded areas that are potential mosquito breeding sites, in an area north of Nairobi, Kenya. Positive results were obtained from a limited test of flood detection in dambos with airborne high resolution L, C, and X band multipolarization synthetic aperture radar (SAR) imagery. L and C bands were effective in detecting flooded dambos, but LHH was by far the best channel for discrimination (p < 0.01) between flooded and nonflooded sites in both sedge and short grass environments. This study demonstrates the feasibility of a combined passive and active remote sensing program for monitoring the location and condition of RVF vector habitats, thus making future control of the disease more promising.     

Robust outdoor visual localization using a three‐dimensional‐edge map

Visual localization systems that are practical for autonomous vehicles in outdoor industrial applications must perform reliably in a wide range of conditions. Changing outdoor conditions cause difficulty by drastically altering the information available in the camera images. To confront the problem, we have developed a visual localization system that uses a surveyed three‐dimensional (3D)‐edge map of permanent structures in the environment. The map has the invariant properties necessary to achieve long‐term robust operation. Previous 3D‐edge map localization systems usually maintain a single pose hypothesis, making it difficult to initialize without an accurate prior pose estimate and also making them susceptible to misalignment with unmapped edges detected in the camera image. A multihypothesis particle filter is employed here to perform the initialization procedure with significant uncertainty in the vehicle's initial pose. A novel observation function for the particle filter is developed and evaluated against two existing functions. The new function is shown to further improve the abilities of the particle filter to converge given a very coarse estimate of the vehicle's initial pose. An intelligent exposure control algorithm is also developed that improves the quality of the pertinent information in the image. Results gathered over an entire sunny day and also during rainy weather illustrate that the localization system can operate in a wide range of outdoor conditions. The conclusion is that an invariant map, a robust multihypothesis localization algorithm, and an intelligent exposure control algorithm all combine to enable reliable visual localization through challenging outdoor conditions. © 2009 Wiley Periodicals, Inc.